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          数据库索引
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        <h2 id="为什么要使用索引"><a href="#为什么要使用索引" class="headerlink" title="为什么要使用索引"></a>为什么要使用索引</h2><p>快速查询数据。</p>
<a id="more"></a>

<h2 id="什么样的信息能成为索引"><a href="#什么样的信息能成为索引" class="headerlink" title="什么样的信息能成为索引"></a>什么样的信息能成为索引</h2><p>能把数据记录限定在一定查找范围的字段(主键、唯一键以及普通键等)。</p>
<h2 id="索引的数据结构"><a href="#索引的数据结构" class="headerlink" title="索引的数据结构"></a>索引的数据结构</h2><p>一般使用B+树做存储索引。</p>
<p>B+树一些主要的特点：</p>
<ul>
<li>字数指针和关键字个数相同（读写代价更低）</li>
<li>非叶节点的字数指针P[i]，指向关键字值[K[i], K[i+1]）的子树</li>
<li>非叶节点仅用来做索引，数据都保存在叶子节点 （查询效果更稳定）</li>
<li>每个叶子节点都有一个指针指向下一个叶子节点(便于选择指定区间的元素，有利于对数据库进行扫描)</li>
</ul>
<p>优点：</p>
<ul>
<li>B+树的读写代价更低</li>
<li>B+树的查询效率更稳定</li>
<li>B+树更有利于对数据库进行扫描</li>
</ul>
<p>Hash表优点和缺点：</p>
<ul>
<li>优点<ul>
<li>B+树需要执行多次IO操作才能找到目标的数据记录，而Hash表只需进行一次IO操作</li>
</ul>
</li>
<li>缺点<ul>
<li>仅能满足=、“IN”操作，不能进行范围查询（&lt;、&gt;、between and）。</li>
<li>不能用来避免数据的排序操作</li>
<li>不能进行部分索引键的查询</li>
<li>不能避免表的扫描</li>
<li>遇到大量数据的hash值相同时，可能效率会低于B+树</li>
</ul>
</li>
</ul>
<h2 id="密集索引和稀疏索引"><a href="#密集索引和稀疏索引" class="headerlink" title="密集索引和稀疏索引"></a>密集索引和稀疏索引</h2><h3 id="密集索引"><a href="#密集索引" class="headerlink" title="密集索引"></a>密集索引</h3><p>每个数据记录的键值分别对应一个索引项</p>
<h3 id="稀疏索引"><a href="#稀疏索引" class="headerlink" title="稀疏索引"></a>稀疏索引</h3><ul>
<li>只有一部分数据记录的键值有索引项对应。</li>
<li>为了定位一条数据记录，需要首先找到小于等于目标记录的最大索引，之后从这一项开始进行顺序遍历，直到找到目标记录为止。</li>
</ul>
<h3 id="区别"><a href="#区别" class="headerlink" title="区别"></a>区别</h3><p>稠密索引的查询速度更快，稀疏索引占用的空间更小，且更容易插入和删除等。</p>

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